Newton experienced in 2009 and checked when thenovelty detection prototype would have been able todetect the anomaly. Here is an excerpt of the paperthat describes the anomaly and measures taken bythe FCT (flight control team) to cope with it (Panta-leoni et al. 2010):We noticed that the thermostat T6073 started to havea strange behavior since mid-May 2009, already 2months before the failure was spotted. The thermostatrange reduced the temperature where it opened andstarted to decrease, a sign of a deterioration of the highthreshold, even if the bottom limit was respected quitewell, until mid-July, when the upper limit and thelower limit went very close to each other. The ther-mostat started to oscillate, in a narrow temperaturerange, until it did not close anymore at the correcttemperature, and it let the temperature go down toalmost 22 deg. This first temperature drop was notspotted because it did not generate any OOL. Afterthat the thermostat had some cycles with a nominalbehavior, but on 13 July 2009 the temperature wentdown deeper, to 21. 25, triggering an OOL and allow-ing the FCT to spot the problem.

We configured the novelty detection prototype to
consider data in the range (January 2009, March
2009) as nominal. We used as time period 48 hours
since it is the duration of an XMM-Newton orbit.
Then we run the novelty detection prototype for the
period (April 2009, July 2009). The results is that the
novelty detection prototype managed to find unusual behavior 2 months before the out-of-limit triggered. This is remarkable not only because it allows
to react to anomalies early, but also because it matches flight control engineers diagnosis results and mimics the effect of having somebody looking every day
at every parameter and noticing if something new is
happening. Figure 5 shows where the OOL triggered
and where the novel behavior was found.

Another tests related with caging was performedwith the novelty detection prototype. In the XMMFCT’s words:XMM reaction wheel 1 faces unexpected increases intorque and current consumption during stable point-ing. The reaction wheel 1 of XMM suffers from anincrement of friction. The possible cause is cage insta-bility due to under-lubrication, Rosetta, another space-craft, also suffered from the same problem. The Roset-ta manufacturer pointed to under-lubrication as apossible cause. Since this anomalous phenomenonhas been spotted, the damaged reaction wheel hasbeen closely monitored. The XMM FCT wanted toknow if the novelty detection could have been able todetect the caging earlier than the flight control teamdid?

For this test, nominal data was defined as the month
of May 2005 when no caging was present. May 2010
was investigated for caging on parameter A5249. The
parameter A5249 refers to the torque of the reaction
wheel 1. Caging has effectively been detected and the
probabilities computed are high enough to be seriously considered. In the end, if the XMM flight control team could have used novelty detection beforehand, the caging phenomenon would have been
detected and closely monitored earlier. The lifetime of
the damaged wheel could have been saved thanks to
an earlier relubrication.

Currently, the novelty detection prototype checks
every day around 2000 XMM-Newton housekeeping
telemetry parameters and reports which of them, if
any, has a new behavior. The results are sorted by
probability of certainty of being a new behavior. The
novelty detection for XMM is integrated in a wider
scope project, XMM early warning system (XEWS)
(Kirsch et al. 2012). XEWS is developed to perform
near real-time trend analysis of spacecraft parameters
in order to detect early degradation of components.
XEWS will enable the mission to perform early countermeasures in case degradation is detected.

In addition, the novelty detection prototype has
been integrated as a plug-in of WebMUST (Oliveira et
al. 2012). WebMUST is a web-based interface to
access telemetry and ancillary data in the MUST
(Martínez-Heras et al. 2005, Baumgartner et al. 2005)
Repository. WebMUST allows users to very efficiently create plots and reports. WebMUST can also sup-

Novelties found for Venus Express using the novelty detection prototype for verifying expected new behavior. The format of the file output is the probability of being an outlier, whether this parameter had data gaps during this period, the start time of the period (in two time
formats), parameter mnemonic, and parameter description.